Gut microbial biomarkers for major depressive disorder: a cross-sectional study.

Background: Alterations in the gut microbiota have been associated with a variety of psychiatric disorders, including major depressive disorder (MDD). However, the relationship between MDD and gut microbial communities remains incompletely understood. Most previous studies have primarily focused on gut bacteria, with relatively limited attention to other microbial components. Methods: In this study, we analyzed gut microbial profiles from 36 patients with MDD and 36 healthy controls using metagenomic sequencing data. The MaAsLin2 algorithm was applied to identify potential microbial biomarkers associated with MDD. Results: A total of 6 bacterial biomarkers and 7 viral biomarkers were identified. The models based on these features demonstrated strong predictive performance, with area under the curve (AUC) values of 0.891 for bacteria and 0.878 for viruses. Notably, the combined bacterial-viral model achieved an AUC of 0.946. These findings were further evaluated through external testing in two unrelated research cohorts. In the Shanxi cohort, the AUC values were 0.825 (bacteria), 0.803 (viruses), and 0.972 (combined model). In the Wuhan cohort, the AUC values were 0.683 (bacteria), 0.693 (viruses), and 0.784 (combined model). Conclusion: In summary, our results highlight the potential of gut bacterial and viral biomarkers as candidate biomarkers and potential auxiliary tools for MDD assessment and suggest that integrating multi-domain microbial features may improve prediction accuracy.